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10 - A Practical Guide for Designing and Conducting Cognitive Studies in Child Psychopathology

from Part III - Experimental and Biological Approaches

Published online by Cambridge University Press:  23 March 2020

Aidan G. C. Wright
Affiliation:
University of Pittsburgh
Michael N. Hallquist
Affiliation:
Pennsylvania State University
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Summary

The chapter discusses the scientific and pragmatic challenges to be addressed when planning a study of cognitive psychopathology in children. The quasi-experimental nature of this branch of inquiry necessitates careful consideration of the sampling frame, as well as decisions on how to validly and efficiently measure psychopathology. The design should focus on maximizing the internal validity of the cognitive construct, experimental manipulation, and outcome variables. However, the ultimate significance of a study is also directly related its relevance to real world behaviors of interest. Pragmatic solutions to establishing effective recruitment strategies as well as methods to train research assistants and maintain active assent among child participants with emotional and behavioral concerns are also discussed.

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Publisher: Cambridge University Press
Print publication year: 2020

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References

Abikoff, H., Courtney, M., Pelham, W. E. Jr., & Koplewicz, H. S. (1993). Teachers’ Ratings of Disruptive Behaviors: The Influence of Halo Effects. Journal of Abnormal Child Psychology, 21(5), 519533.CrossRefGoogle ScholarPubMed
Achenbach, T. M., McConaughy, S. H., & Howell, C. T. (1987). Child Adolescent Behavioral and Emotional Problems: Implications of Cross-Informant Correlations for Situational Specificity. Psychological Bulletin, 101(2), 213232.Google Scholar
Achenbach, T. M., Krukowski, R. A., Dumenci, L., & Ivanova, M. Y. (2005). Assessment of Adult Psychopathology: Meta-Analyses and Implications of Cross-Informant Correlations. Psychological Bulletin, 131(3), 361382.CrossRefGoogle ScholarPubMed
Barkley, R. A. (1997). Behavioral Inhibition, Sustained Attention, and Executive Functions: Constructing a Unifying Theory of ADHD. Psychological Bulletin, 121(1), 6594.Google Scholar
Baron-Cohen, S., Leslie, A. M., & Frith, U. (1986). Mechanical, Behavioral, and Intentional Understanding of Picture Stories in Autistic Children. British Journal of Developmental Psychology, 4, 113125.Google Scholar
Basco, M. R., Bostic, J. Q., Davies, D., Rush, A. J., Witte, B., Hendrickse, W., & Barnett, V. (2000). Methods to Improve Diagnostic Accuracy in a Community Mental Health Setting. American Journal of Psychiatry, 157(10), 15991605.Google Scholar
Bentall, R. P. (1996). At the Centre of a Science of Psychopathology? Characteristics and Limitations of Cognitive Research. Cognitive Neuropsychiatry, 1(4), 265273.CrossRefGoogle ScholarPubMed
Berkson, J. (1946). Limitations of the Application of Fourfold Table Analysis to Hospital Data. Biometrics Bulletin, 2(3), 4753.Google Scholar
Bilder, R. M., Howe, A., Novak, N., Sabb, F. W., & Parker, D. S. (2011). The Genetics of Cognitive Impairment in Schizophrenia: A Phenomic Perspective. Trends in Cognitive Sciences, 15(9), 428435.Google Scholar
Bird, H. R., Gould, M. S., & Staghezza, B. (1992). Aggregating Data from Multiple Informants in Child Psychiatry Epidemiologic Research. Journal of the American Academy of Child and Adolescent Psychiatry, 31(1), 7885.Google Scholar
Boonstra, A. M., Oosterlaan, J., Sergeant, J. A., & Buitelaar, J. K. (2005). Executive Functioning in Adult ADHD: A Meta-Analytic Review. Psychological Medicine, 35(8), 10971108.Google Scholar
Brown, S. D., & Heathcote, A. (2008). The Simplest Complete Model of Choice Response Time: Linear Ballistic Accumulation. Cognitive Psychology, 57(3), 153178.Google Scholar
Brunshaw, J. M., & Szatmari, P. (1988). The Agreement between Behaviour Checklists and Structured Psychiatric Interviews for Children. Canadian Journal of Psychiatry, 33(6), 474481.Google Scholar
Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., … Moffitt, T. E. (2014). The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? Clinical Psychological Science, 2(2), 119137.Google Scholar
Clay, C., Ellis, M. A., Amodeo, M., Fassler, I., & Griffin, M. L. (2003). Recruiting a Community Sample of African American Subjects: The Nuts and Bolts of a Successful Effort. Families in Society – The Journal of Contemporary Human Services, 84(3), 396404.Google Scholar
Cohen, P., & Cohen, J. (1984). The Clinician’s Illusion. Archives of General Psychiatry, 41(12), 11781182.Google Scholar
Cohen-Gilbert, J. E., Killgore, W. D. S., White, C. N., Schwab, Z. J., Crowley, D. J., Covell, M. J., … Silveri, M. M. (2014). Differential Influence of Safe versus Threatening Facial Expressions on Decision-Making during an Inhibitory Control Task in Adolescence and Adulthood. Developmental Science, 17(2), 212223.Google Scholar
Conners, C. K., Erhardt, D., & Sparrow, E. P. (1999). Conners’ Adult ADHD Rating Scales (CAARS): Technical Manual. Toronto: Multi-Health Systems.Google Scholar
Conway, A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working Memory Span Tasks: A Methodological Review and User’s Guide. Psychonomic Bulletin & Review, 12(5), 769786.Google Scholar
Corbie-Smith, G., Thomas, S. B., & St. George, D. M. M. (2002). Distrust, Race, and Research. Archives of Internal Medicine, 162(21), 24582463.Google Scholar
Costello, E. J., Mustillo, S., Erkanli, A., Keeler, G., & Angold, A. (2003). Prevalence and Development of Psychiatric Disorders in Childhood and Adolescence. Archives of General Psychiatry, 60(8), 837844.Google Scholar
Dantas, O. M., Ximenes, R. A., de Albuquerque, M. d. F. P., Montarroyos, U. R., de Souza, W. V., Varejão, P., & Rodrigues, L. C. (2007). Selection Bias: Neighbourhood Controls and Controls Selected from Those Presenting to a Health Unit in a Case Control Study of Efficacy of BCG Revaccination. BMC Medical Research Methodology, 7(1), 11.Google Scholar
Dawson, M. R. W. (1988). Fitting the Ex-Gaussian Equation to Reaction Time Distributions. Behavior Research Methods Instruments & Computers, 20(1), 5457.Google Scholar
De Los Reyes, A., Thomas, S. A., Goodman, K. L., & Kundey, S. M. A. (2013). Principles Underlying the Use of Multiple Informants’ Reports. Annual Review of Clinical Psychology, 9(9), 123149.Google Scholar
De Los Reyes, A., Augenstein, T. M., Wang, M., Thomas, S. A., Drabick, D. A. G., Burgers, D. E., & Rabinowitz, J. (2015). The Validity of the Multi-Informant Approach to Assessing Child and Adolescent Mental Health. Psychological Bulletin, 141(4), 858900.Google Scholar
Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and Educational Achievement. Intelligence, 35(1), 1321.Google Scholar
Doyle, A., Ostrander, R., Skare, S., Crosby, R. D., & August, G. J. (1997). Convergent and Criterion-Related Validity of the Behavior Assessment System for Children-Parent Rating Scale. Journal of Clinical Child Psychology, 26(3), 276284.Google Scholar
Dudeney, J., Sharpe, L., & Hunt, C. (2015). Attentional Bias towards Threatening Stimuli in Children with Anxiety: A Meta-Analysis. Clinical Psychology Review, 40, 6675.Google Scholar
Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. (1999). Working Memory, Short-Term Memory, and General Fluid Intelligence: A Latent-Variable Approach. Journal of Experimental Psychology-General, 128(3), 309331.Google Scholar
Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., … Altaye, M. (2011). Evidence for Higher Reaction Time Variability for Children with ADHD on a Range of Cognitive Tasks including Reward and Event Rate Manipulations. Neuropsychology, 25(4), 427441.Google Scholar
Farmer, D. F., Jackson, S. A., Camacho, F., & Hall, M. A. (2007). Attitudes of African American and Low Socioeconomic Status White Women toward Medical Research. Journal of Health Care for the Poor and Underserved, 18(1), 8599.Google Scholar
Fombonne, E. (2009). Epidemiology of Pervasive Developmental Disorders. Pediatric Research, 65(6), 591598.Google Scholar
Garnier-Villarreal, M., Rhemtulla, M., & Little, T. D. (2014). Two-Method Planned Missing Designs for Longitudinal Research. International Journal of Behavioral Development, 38(5), 411422.Google Scholar
Geary, D. C. (2011). Cognitive Predictors of Achievement Growth in Mathematics: A 5-Year Longitudinal Study. Developmental Psychology, 47(6), 15391552.Google Scholar
Gibbons, R. D., Weiss, D. J., Frank, E., & Kupfer, D. (2016). Computerized Adaptive Diagnosis and Testing of Mental Health Disorders. Annual Review of Clinical Psychology, 12(1), 83104.Google Scholar
Gilmore, R. O., & Adolph, K. E. (2017). Video Can Make Science More Open, Transparent, Robust, and Reproducible. Retrieved from https://psyarxiv.com/tcfqf/Google Scholar
Gilmore, R. O., Diaz, M. T., Wyble, B. A., & Yarkoni, T. (2017). Progress toward Openness, Transparency, and Reproducibility in Cognitive Neuroscience. Annals of the New York Academy of Sciences, 1396(1), 518.Google Scholar
Golden, C. J., Fishburne, F. J., Lewis, G. P., Conley, F. K., Moses, J. A., Engum, E., … Graber, B. (1981). Cross-Validation of the Luria-Nebraska Neuropsychological Battery for the Presence, Lateralization, and Localization of Brain-Damage. Journal of Consulting and Clinical Psychology, 49(4), 491507.Google Scholar
Goodman, S. H., Lahey, B. B., Fielding, B., Dulcan, M., Narrow, W., & Regier, D. (1997). Representativeness of Clinical Samples of Youths with Mental Disorders: A Preliminary Population-Based Study. Journal of Abnormal Psychology, 106(1), 314.Google Scholar
Gottesman, I. I., & Gould, T. D. (2003). The Endophenotype Concept in Psychiatry: Etymology and Strategic Intentions. American Journal of Psychiatry, 160(4), 636645.Google Scholar
Graham, J. W. (2012). Missing Data: Analysis and Design. New York: Springer.Google Scholar
Graham, J. W., Taylor, B. J., Olchowski, A. E., & Cumsille, P. E. (2006). Planned Missing Data Designs in Psychological Research. Psychological Methods, 11(4), 323343.Google Scholar
Grimes, D. A., & Schulz, K. F. (2005). Compared to What? Finding Controls for Case-Control Studies. Lancet, 365(9468), 14291433.Google Scholar
Grobbee, D., & Hoes, A. (2015). Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research. Burlington, MA: Jones and Bartlett Learning, LLC.Google Scholar
Halperin, J. M. (2016). Executive Functioning – A Key Construct for Understanding Developmental Psychopathology or a “Catch-All” Term in Need of Some Rethinking? Journal of Child Psychology and Psychiatry, 57(4), 443445.Google Scholar
Halperin, J. M., Wolf, L., Greenblatt, E. R., & Young, G. (1991). Subtype Analysis of Commission Errors on the Continuous Performance Test in Children. Developmental Neuropsychology, 7(2), 207217.Google Scholar
Hart, E. L., Lahey, B. B., Loeber, R., & Hanson, K. S. (1994). Criterion Validity of Informants in the Diagnosis of Disruptive Behavior Disorders in Children: A Preliminary Study. Journal of Consulting and Clinical Psychology, 62(2), 410414.Google Scholar
Hartung, C. M., Van Pelt, J. C., Armendariz, M. L., & Knight, L. A. (2006). Biases in Ratings of Disruptive Behavior in Children: Effects of Sex and Negative Halos. Journal of Attention Disorders, 9(4), 620630.Google Scholar
Haywood, H. C., & Raffard, S. (2017). Cognition and Psychopathology: Overview. Journal of Cognitive Education and Psychology, 16(1), 38.Google Scholar
Hill, E. L. (2004). Executive Dysfunction in Autism. Trends in Cognitive Sciences, 8(1), 2632.Google Scholar
Hinshaw, S. P., & Nigg, J. T. (1999). Behavior Rating Scales in the Assessment of Disruptive Behavior Problems in childhood. In Shaffer, D., Lucas, C. P., & Richters, J. E. (Eds.), Diagnostic Assessment in Child and Adolescent Psychopathology (pp. 91126). New York: Guilford Press.Google Scholar
Hohmann, A. A., & Parron, D. L. (1996). How the New NIH Guidelines on Inclusion of Women and Minorities Apply: Efficacy Trials, Effectiveness Trials, and Validity. Journal of Consulting and Clinical Psychology, 64(5), 851855.Google Scholar
Huang-Pollock, C., & Nigg, J. T. (2003). Searching for the Attention Deficit in Attention Deficit Hyperactivity Disorder: The Case of Visuospatial Orienting. Clinical Psychology Review, 23(6), 801830.Google Scholar
Huang-Pollock, C., Nigg, J. T., & Halperin, J. M. (2006). Single Dissociation Findings of ADHD Deficits in Vigilance but not Anterior or Posterior Attention Systems. Neuropsychology, 20(4), 420429.Google Scholar
Huang-Pollock, C. L., Karalunas, S. L., Tam, H., & Moore, A. N. (2012). Evaluating Vigilance Deficits in ADHD: A Meta-Analysis of CPT Performance. Journal of Abnormal Psychology, 121(2), 360371.Google Scholar
Huang-Pollock, C., Ratcliff, R., McKoon, G., Shapiro, Z., Weigard, A., & Galloway-Long, H. (2017a). Using the Diffusion Model to Explain Cognitive Deficits in Attention Deficit Hyperactivity Disorder. Journal of Abnormal Child Psychology, 45(1), 5768.Google Scholar
Huang-Pollock, C., Shapiro, Z., Galloway-Long, H., & Weigard, A. (2017b). Is Poor Working Memory a Transdiagnostic Risk Factor for Psychopathology? Journal of Abnormal Child Psychology, 45(8), 14771490.Google Scholar
Hunsley, J., & Meyer, G. J. (2003). The Incremental Validity of Psychological Testing and Assessment: Conceptual, Methodological, and Statistical Issues. Psychological Assessment, 15(4), 446455.CrossRefGoogle ScholarPubMed
Ibrahim, M. A., & Spitzer, W. O. (1979). Case Control Study: Problem and the Prospect. Journal of Chronic Diseases, 32(1‒2), 139144.Google Scholar
Jacoby, L. L. (1991). A Process Dissociation Framework – Separating Automatic from Intentional Uses of Memory. Journal of Memory and Language, 30(5), 513541.Google Scholar
Jensen-Doss, A., & Hawley, K. M. (2010). Understanding Barriers to Evidence-Based Assessment: Clinician Attitudes toward Standardized Assessment Tools. Journal of Clinical Child and Adolescent Psychology, 39(6), 885896.CrossRefGoogle ScholarPubMed
Jensen, P. S., Rubio-Stipec, M., Canino, G., Bird, H. R., Dulcan, M. K., Schwab-Stone, M. E., & Lahey, B. B. (1999). Parent and Child Contributions to Diagnosis of Mental Disorder: Are Both Informants Always Necessary? Journal of the American Academy of Child and Adolescent Psychiatry, 38(12), 15691579.Google Scholar
Johnston, C., & Murray, C. (2003). Incremental Validity in the Psychological Assessment of Children and Adolescents. Psychological Assessment, 15(4), 496507.Google Scholar
Karalunas, S. L., & Huang-Pollock, C. L. (2013). Integrating Impairments in Reaction Time and Executive Function Using a Diffusion Model Framework. Journal of Abnormal Child Psychology, 41(5), 837850.Google Scholar
Karalunas, S. L., Huang-Pollock, C. L., & Nigg, J. T. (2012). Decomposing Attention-Deficit/Hyperactivity Disorder (ADHD)-Related Effects in Response Speed and Variability. Neuropsychology, 26(6), 684694.Google Scholar
Karalunas, S. L., Geurts, H. M., Konrad, K., Bender, S., & Nigg, J. T. (2014). Annual Research Review: Reaction Time Variability in ADHD and Autism Spectrum Disorders: Measurement and Mechanisms of a Proposed Trans-Diagnostic Phenotype. Journal of Child Psychology and Psychiatry, 55(6), 685710.Google Scholar
Klein, D. N., Dougherty, L. R., & Olino, T. M. (2005). Toward Guidelines for Evidence-Based Assessment of Depression in Children and Adolescents. Journal of Clinical Child & Adolescent Psychology, 34(3), 412432.Google Scholar
Klin, A. (2000). Attributing Social Meaning to Ambiguous Visual Stimuli in Higher-Functioning Autism and Asperger Syndrome: The Social Attribution Task. Journal of Child Psychology and Psychiatry and Allied Disciplines, 41(7), 831846.Google Scholar
Kopec, J. A., & Esdaile, J. M. (1990). Bias in Case Control Studies, A Review. Journal of Epidemiology and Community Health, 44(3), 179186.Google Scholar
Kozak, M. J., & Cuthbert, B. N. (2016). The NIMH Research Domain Criteria Initiative: Background, Issues, and Pragmatics. Psychophysiology, 53(3), 286297.Google Scholar
Kraemer, H. C., Measelle, J. R., Ablow, J. C., Essex, M. J., Boyce, W. T., & Kupfer, D. J. (2003). A New Approach to Integrating Data from Multiple Informants in Psychiatric Assessment and Research: Mixing and Matching Contexts and Perspectives. American Journal of Psychiatry, 160(9), 15661577.Google Scholar
Lacouture, Y., & Cousineau, D. (2008). How to Use MATLAB to Fit the Ex-Gaussian and Other Probability Functions to a Distribution of Response Times. Tutorials in Quantitative Methods for Psychology, 4(1), 3545.Google Scholar
Lahey, B. B., Applegate, B., Barkley, R. A., Garfinkel, B., McBurnett, K., Kerdyk, L., … Shaffer, D. (1994a). DSM-IV Field Trials for Oppositional Defiant Disorder and Conduct Disorder in Children and Adolescents. American Journal of Psychiatry, 151(8), 11631171.Google Scholar
Lahey, B. B., Applegate, B., McBurnett, K., Biederman, J., Greenhill, L., Hynd, G. W., … Shaffer, D. (1994b). DSM-IV Field Trials for Attention-Deficit Hyperactivity Disorder in Children and Adolescents. American Journal of Psychiatry, 151(11), 16731685.Google ScholarPubMed
Levin-Aspenson, H. F., & Watson, D. (2018). Mode of Administration Effects in Psychopathology Assessment: Analyses of Gender, Age, and Education Differences in Self-Rated versus Interview-Based Depression. Psychological Assessment, 30(3), 287295.Google Scholar
Lijffijt, M., Kenemans, J. L., Verbaten, M. N., & van Engeland, H. (2005). A Meta-Analytic Review of Stopping Performance in Attention-Deficit/Hyperactivity Disorder: Deficient Inhibitory Motor Control? Journal of Abnormal Psychology, 114(2), 216222.Google Scholar
Little, T. D., & Rhemtulla, M. (2013). Planned Missing Data Designs for Developmental Researchers. Child Development Perspectives, 7(4), 199204.Google Scholar
Logan, G. D., Van Zandt, T., Verbruggen, F., & Wagenmakers, E.-J. (2014). On the Ability to Inhibit Thought and Action: General and Special Theories of an Act of Control. Psychological Review, 121(1), 6695.Google Scholar
Longwell, B. T., & Truax, P. (2005). The Differential Effects of Weekly, Monthly, and Bimonthly Administrations of the Beck Depression Inventory-II: Psychometric Properties and Clinical Implications. Behavior Therapy, 36(3), 265275.Google Scholar
Lumsden, J., Edwards, E. A., Lawrence, N. S., Coyle, D., & Munafo, M. R. (2016). Gamification of Cognitive Assessment and Cognitive Training: A Systematic Review of Applications and Efficacy. Journal of Medical Internet Research Serious Games, 4(2), 14.Google Scholar
Lund, E. (1989). The Validity of Different Control Groups in a Case-Control Study: Oral Contraceptive Use and Breast Cancer in Young Women. Journal of Clinical Epidemiology, 42(10), 987993.Google Scholar
Ma, X. M., Buffler, P. A., Layefsky, M., Does, M. B., & Reynolds, P. (2004). Control Selection Strategies in Case-Control Studies of Childhood Diseases. American Journal of Epidemiology, 159(10), 915921.Google Scholar
Magnússon, P., Smári, J., Sigurðardóttir, D., Baldursson, G., Sigmundsson, J., Kristjánsson, K., … Guðmundsson, Ó. Ó. (2006). Validity of Self-Report and Informant Rating Scales of Adult ADHD Symptoms in Comparison with a Semistructured Diagnostic Interview. Journal of Attention Disorders, 9(3), 494503.Google Scholar
Martel, M. M., Schimmack, U., Nikolas, M., & Nigg, J. T. (2015). Integration of Symptom Ratings from Multiple Informants in ADHD Diagnosis: A Psychometric Model with Clinical Utility. Psychological Assessment, 27(3), 10601071.Google Scholar
Martin, A., Rief, W., Klaiberg, A., & Braehler, E. (2006). Validity of the Brief Patient Health Questionnaire Mood Scale (PHQ-9) in the General Population. General Hospital Psychiatry, 28(1), 7177.Google Scholar
Martin, R. P., Hooper, S., & Snow, J. (1986). Behavior Rating Scale Approaches to Personality Assessment in Children and Adolescents. In Knoff, H. M. (Ed.), The Assessment of Child and Adolescent Personality (pp. 309348). New York: Guilford Press.Google Scholar
Masten, A. S., Hubbard, J. J., Gest, S. D., Tellegen, A., Garmezy, N., & Ramirez, M. (1999). Competence in the Context of Adversity: Pathways to Resilience and Maladaptation from Childhood to Late Adolescence. Development and Psychopathology, 11(1), 143169.Google Scholar
Matzke, D., Love, J., Wiecki, T. V., Brown, S. D., Logan, G. D., & Wagenmakers, E. J. (2013). Release the BEESTS: Bayesian Estimation of Ex-Gaussian Stop Signal Reaction Time Distributions. Frontiers in Psychology, 4, 918.Google Scholar
McTeague, L. M., Huemer, J., Carreon, D. M., Jiang, Y., Eickhoff, S. B., & Etkin, A. (2017). Identification of Common Neural Circuit Disruptions in Cognitive Control across Psychiatric Disorders. American Journal of Psychiatry, 174(7), 676685.Google Scholar
Moffitt, T. E. (1993). Adolescence-Limited and Life-Course Persistent Antisocial Behavior: A Developmental Taxonomy. Psychological Review, 100(4), 674701.Google Scholar
Mulder, M. J., Bos, D., Weusten, J. M. H., van Belle, J., van Dijk, S. C., Simen, P., … Durston, S. (2010). Basic Impairments in Regulating the Speed-Accuracy Tradeoff Predict Symptoms of Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry, 68(12), 11141119.Google Scholar
Nieuwenstein, M. R., Aleman, A., & de Haan, E. H. F. (2001). Relationship between Symptom Dimensions and Neurocognitive Functioning in Schizophrenia: A Meta-Analysis of WCST and CPT Studies. Journal of Psychiatric Research, 35(2), 119125.Google Scholar
Nigg, J. T., Blaskey, L. G., Stawicki, J. A., & Sachek, J. (2004). Evaluating the Endophenotype Model of ADHD Neuropsychological Deficit: Results for Parents and Siblings of Children with ADHD Combined and Inattentive Subtypes. Journal of Abnormal Psychology, 113(4), 614625.Google Scholar
Nigg, J. T., Willcutt, E. G., Doyle, A., & Sonuga-Barke, E. J. S. (2005). Causal Heterogeneity in Attention-Deficit/Hyperactivity Disorder: Do We Need Neuropsychologically Impaired Subtypes? Biological Psychiatry, 57(11), 12241230.Google Scholar
Nigg, J. T., Jester, J. M., Stavro, G. M., Ip, K. I., Puttler, L. I., & Zucker, R. A. (2017). Specificity of Executive Functioning and Processing Speed Problems in Common Psychopathology. Neuropsychology, 31(4), 448466.Google Scholar
Nigg, J. T., Gustafsson, H. C., Karalunas, S. L., Ryabinin, P., McWeeney, S. K., Faraone, S. V., … Wilmot, B. (2018). Working Memory and Vigilance as Multivariate Endophenotypes Related to Common Genetic Risk for Attention-Deficit/Hyperactivity Disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 57(3), 175182.Google Scholar
Nolen-Hoeksema, S., & Watkins, E. R. (2011). A Heuristic for Developing Transdiagnostic Models of Psychopathology: Explaining Multifinality and Divergent Trajectories. Perspectives on Psychological Science, 6(6), 589609.Google Scholar
Oosterlaan, J., Logan, G., & Sergeant, J. A. (1998). Response Inhibition in AD/HD, CD, Comorbid AD/HD+CD, Anxious, and Control Children: A Meta-Analysis of Studies with the Stop Task. Journal of Child Psychology and Psychiatry, 39(3), 411425.Google Scholar
Pauli-Pott, U., & Becker, K. (2011). Neuropsychological Basic Deficits in Preschoolers at Risk for ADHD: A Meta-Analysis. Clinical Psychology Review, 31(4), 626637.CrossRefGoogle ScholarPubMed
Pelham, W. E., Jr., Fabiano, G. A., & Massetti, G. M. (2005). Evidence-Based Assessment of Attention Deficit Hyperactivity Disorder in Children and Adolescents. Journal of Clinical Child & Adolescent Psychology, 34(3), 449476.Google Scholar
Pennington, B. F., & Ozonoff, S. (1996). Executive Functions and Developmental Psychopathology. Journal of Child Psychology and Psychiatry, 37(1), 5187.Google Scholar
Polanczyk, G. V., Salum, G. A., Sugaya, L. S., Caye, A., & Rohde, L. A. (2015). Annual Research Review: A Meta-Analysis of the Worldwide Prevalence of Mental Disorders in Children and Adolescents. Journal of Child Psychology and Psychiatry, 56(3), 345365.CrossRefGoogle ScholarPubMed
Quraishi, S., & Frangou, S. (2002). Neuropsychology of Bipolar Disorder: A Review. Journal of Affective Disorders, 72(3), 209226.Google Scholar
Ratcliff, R., & Frank, M. J. (2012). Reinforcement-Based Decision Making in Corticostriatal Circuits: Mutual Constraints by Neurocomputational and Diffusion Models. Neural Computation, 24(5), 11861229.Google Scholar
Ratcliff, R., & McKoon, G. (2008). The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks. Neural Computation, 20(4), 873922.Google Scholar
Ratcliff, R., Thapar, A., & McKoon, G. (2001). The Effects of Aging on Reaction Time in a Signal Detection Task. Psychology and Aging, 16(2), 323341.Google Scholar
Ratcliff, R., Thapar, A., & McKoon, G. (2006). Aging, Practice, and Perceptual Tasks: A Diffusion Model Analysis. Psychology and Aging, 21(2), 353371.Google Scholar
Ratcliff, R., Love, J., Thompson, C. A., & Opfer, J. E. (2012). Children Are Not Like Older Adults: A Diffusion Model Analysis of Developmental Changes in Speeded Responses. Child Development, 83(1), 367381.Google Scholar
Reynolds, W. M., & Kobak, K. A. (1995). Reliability and Validity of the Hamilton Depression Inventory: A Paper-and-Pencil Version of the Hamilton Depression Rating Scale Clinical Interview. Psychological Assessment, 7(4), 472483.Google Scholar
Rhemtulla, M., & Little, T. (2012). Tools of the Trade: Planned Missing Data Designs for Research in Cognitive Development. Journal of Cognition and Development: Official Journal of the Cognitive Development Society, 13(4), 425438.Google Scholar
Richman, W. L., Kiesler, S., Weisb, S., & Drasgow, F. (1999). A Meta-Analytic Study of Social Desirability Distortion in Computer-Administered Questionnaires, Traditional Questionnaires, and Interviews. Journal of Applied Psychology, 84(5), 754775.Google Scholar
Rothman, K. (1986). Modern Epidemiology. Boston: Little, Brown, and Company.Google Scholar
Salum, G. A., Sergeant, J., Sonuga-Barke, E., Vandekerckhove, J., Gadelha, A., Pan, P. M., … Rohde, L. A. P. (2014). Specificity of Basic Information Processing and Inhibitory Control in Attention Deficit Hyperactivity Disorder. Psychological Medicine, 44(3), 617631.Google Scholar
Sanislow, C. A., Pine, D. S., Quinn, K. J., Kozak, M. J., Garvey, M. A., Heinssen, R. K., … Cuthbert, B. N. (2010). Developing Constructs for Psychopathology Research: Research Domain Criteria. Journal of Abnormal Psychology, 119(4), 631639.Google Scholar
Schachar, R., Sandberg, S., & Rutter, M. (1986). Agreement between Teachers’ Ratings and Observations of Hyperactivity, Inattentiveness, and Defiance. Journal of Abnormal Child Psychology, 14(2), 331345.Google Scholar
Schmidt, F. (2010). Detecting and Correcting the Lies that Data Tell. Perspectives on Psychological Science, 5(3), 233242.Google Scholar
Schwartz, K., & Verhaeghen, P. (2008). ADHD and Stroop Interference from Age 9 to Age 41 Years: A Meta-Analysis of Developmental Effects. Psychological Medicine, 38(11), 16071616.Google Scholar
Schwarz, N. (1999). Self-Reports: How the Questions Shape the Answers. American Psychologist, 54(2), 93105.Google Scholar
Seidman, L. J., Biederman, J., Monuteaux, M. C., Weber, W., & Faraone, S. V. (2000). Neuropsychological Functioning in Nonreferred Siblings of Children with Attention Deficit/Hyperactivity Disorder. Journal of Abnormal Psychology, 109(2), 252265.Google Scholar
Shapiro, Z., Huang-Pollock, C. L., Graham, J., & Neely, K. (in press). Making the Most of It: Application of Planned Missingness Design to Increase the Efficiency of Diagnostic Assessment.Google Scholar
Shemmassian, S. K., & Lee, S. S. (2015). Predictive Utility of Four Methods of Incorporating Parent and Teacher Symptom Ratings of ADHD for Longitudinal Outcomes. Journal of Clinical Child & Adolescent Psychology, 45(2), 112.Google Scholar
Silverman, W. K., & Ollendick, T. H. (2005). Evidence-Based Assessment of Anxiety and Its Disorders in Children and Adolescents. Journal of Clinical Child and Adolescent Psychology, 34(3), 380411.Google Scholar
Smith, P. L. (2016). Diffusion Theory of Decision Making in Continuous Report. Psychological Review, 123(4), 425451.Google Scholar
Stavraky, K. M., & Clarke, E. A. (1983). Hospital or Population Controls: An Unanswered Question. Journal of Chronic Diseases, 36(4), 301307.Google Scholar
UyBico, S. J., Pavel, S., & Gross, C. P. (2007). Recruiting Vulnerable Populations into Research: A Systematic Review of Recruitment Interventions. Journal of General Internal Medicine, 22(6), 852863.Google Scholar
Vaughn, A. J., & Hoza, B. (2013). The Incremental Utility of Behavioral Rating Scales and a Structured Diagnostic Interview in the Assessment of Attention-Deficit/Hyperactivity Disorder. Journal of Emotional and Behavioral Disorders, 21(4), 227239.Google Scholar
Vega, A., & Parsons, O. A. (1967). Cross-Validation of Halstead-Reitan Tests for Brain Damage. Journal of Consulting Psychology, 31(6), 619625.Google Scholar
Verbruggen, F., McLaren, I. P. L., & Chambers, C. D. (2014). Banishing the Control Homunculi in Studies of Action Control and Behavior Change. Perspectives on Psychological Science, 9(5), 497524.Google Scholar
Voss, A., Nagler, M., & Lerche, V. (2013). Diffusion Models in Experimental Psychology: A Practical Introduction. Experimental Psychology, 60(6), 385402.CrossRefGoogle ScholarPubMed
Wacholder, S., Silverman, D. T., McLaughlin, J. K., & Mandel, J. S. (1992a). Selection of Controls in case-Control Studies 2: Types of Controls. American Journal of Epidemiology, 135(9), 10291041.Google Scholar
Wacholder, S., Silverman, D. T., McLaughlin, J. K., & Mandel, J. S. (1992b). Selection of Controls in Case-Control Studies 3: Design Options. American Journal of Epidemiology, 135(9), 10421050.Google Scholar
Weigard, A., & Huang-Pollock, C. L. (2014). A Diffusion Modeling Approach to Understanding Contextual Cueing Effects in Children with ADHD. Journal of Child Psychology and Psychiatry, 55(12), 13361344.Google Scholar
Weigard, A., & Huang-Pollock, C. (2017). The Role of Speed in ADHD-Related Working Memory Deficits. Clinical Psychological Science, 5(2), 195211.Google Scholar
Weigard, A., Huang-Pollock, C., & Brown, S. (2016). Evaluating the Consequences of Impaired Monitoring of Learned Behavior in Attention-Deficit/Hyperactivity Disorder Using a Bayesian Hierarchical Model of Choice Response Time. Neuropsychology, 30(4), 502515.Google Scholar
Weigard, A., Huang-Pollock, C., Brown, S., & Heathcote, A. (2018). Testing Formal Predictions of Neuroscientific Theories of ADHD with a Cognitive Model-Based Approach. Journal of Abnormal Psychology, 127(5), 529539.Google Scholar
White, C. N., Ratcliff, R., & Starns, J. J. (2011). Diffusion Models of the Flanker Task: Discrete versus Gradual Attentional Selection. Cognitive Psychology, 63(4), 210238.Google Scholar
White, C. N., Ratcliff, R., Vasey, M. W., & McKoon, G. (2010). Anxiety Enhances Threat Processing without Competition among Multiple Inputs: A Diffusion Model Analysis. Emotion, 10(5), 662677.Google Scholar
White, C. N., Skokin, K., Carlos, B., & Weaver, A. (2015). Using Decision Models to Decompose Anxiety-Related Bias in Threat Classification. Emotion, 16(2), 196207.Google Scholar
White, L. K., Moore, T. M., Calkins, M. E., Wolf, D. H., Satterthwaite, T. D., Leibenluft, E., … Gur, R. E. (2017). An Evaluation of the Specificity of Executive Function Impairment in Developmental Psychopathology. Journal of the American Academy of Child & Adolescent Psychiatry, 56(11), 975982.Google Scholar
Willcutt, E. G., Doyle, A., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the Executive Function Theory of Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review. Biological Psychiatry, 57(11), 13361346.Google Scholar
Yeargin-Allsopp, M., Rice, C., Karapurkar, T., Doernberg, N., Boyle, C., & Murphy, C. (2003). Prevalence of Autism in a US Metropolitan Area. Journal of the American Medical Association, 289(1), 4955.Google Scholar
Yirmiya, N., Erel, O., Shaked, M., & Solomonica-Levi, D. (1998). Meta-Analyses Comparing Theory of Mind Abilities of Individuals with Autism, Individuals with Mental Retardation, and Normally Developing Individuals. Psychological Bulletin, 124(3), 283307.Google Scholar
Zawadzki, M. J., Graham, J. W., & Gerin, W. (2012). Increasing the Validity and Efficiency of Blood Pressure Estimates Using Ambulatory and Clinic Measurements and Modern Missing Data Methods. American Journal of Hypertension, 25(7), 764769.Google Scholar
Zvolensky, M., Forsyth, J., & Johnson, K. (2013). Laboratory Methods in Experimental Psychopathology. In Comer, J. S. & Kendall, P. C. (Eds.), The Oxford Handbook of Research Strategies for Clinical Psychology. New York: Oxford University Press.Google Scholar

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